Triple
T15690038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Menken |
E380303
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Matthew Weiner |
E268664
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Matthew Weiner | Statement: [Rachel Menken, createdBy, Matthew Weiner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Weiner Context triple: [Rachel Menken, createdBy, Matthew Weiner]
-
A.
Matthew Weiner
chosen
Matthew Weiner is an American television writer, director, and producer best known for creating the critically acclaimed series "Mad Men."
-
B.
Sam Levinson
Sam Levinson is an American filmmaker, screenwriter, and director best known for creating the HBO teen drama series "Euphoria."
-
C.
John Slattery
John Slattery is an American actor and director best known for his role as Roger Sterling on the television series "Mad Men."
-
D.
Donald Faison
Donald Faison is an American actor and comedian best known for his role as Dr. Christopher Turk on the television series "Scrubs."
-
E.
David Margulies
David Margulies was an American character actor known for his roles in films such as Ghostbusters and numerous appearances on stage and television.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4e59988190aaf12f6a07c8f0e4 |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6eebaccc8190a61fb2f9b9bdbcc1 |
completed | May 9, 2026, 5:29 p.m. |
Created at: April 10, 2026, 4:44 a.m.